Codebooks for dataset
Making the codebook
Here, we’re just setting a few options.
knitr::opts_chunk$set(
warning = TRUE, # show warnings during codebook generation
message = TRUE, # show messages during codebook generation
error = TRUE, # do not interrupt codebook generation in case of errors,
# usually better for debugging
echo = TRUE # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())## Warning: replacing previous import 'vctrs::data_frame' by 'tibble::data_frame'
## when loading 'dplyr'Now, we’re preparing our data for the codebook.
library(codebook)
webshot::install_phantomjs()## It seems that the version of `phantomjs` installed is greater than or equal to the requested version.To install the requested version or downgrade to another version, use `force = TRUE`.library(labelled)##
## Attaching package: 'labelled'## The following object is masked from 'package:codebook':
##
## to_factorlibrary(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union# codebook_data <- codebook::bfi
# to import an SPSS file from the same folder uncomment and edit the line below
# codebook_data <- rio::import("mydata.sav")
# for Stata
# codebook_data <- rio::import("mydata.dta")
# for CSV
codebook_data_prep <- rio::import("peril_data_deid.csv")
v1 <- which(names(codebook_data_prep) == 'control_1') #find first column
v2 <- which(names(codebook_data_prep) == 'control_deep') #find last column
codebook_data <- codebook_data_prep %>%
mutate_at(c(v1:v2),as.numeric)## Warning: Problem with `mutate()` input `control_1`.
## x NAs introduced by coercion
## ℹ Input `control_1` is `.Primitive("as.double")(control_1)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `control_2`.
## x NAs introduced by coercion
## ℹ Input `control_2` is `.Primitive("as.double")(control_2)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `fam1`.
## x NAs introduced by coercion
## ℹ Input `fam1` is `.Primitive("as.double")(fam1)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `fam2`.
## x NAs introduced by coercion
## ℹ Input `fam2` is `.Primitive("as.double")(fam2)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `fam3`.
## x NAs introduced by coercion
## ℹ Input `fam3` is `.Primitive("as.double")(fam3)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `fam4`.
## x NAs introduced by coercion
## ℹ Input `fam4` is `.Primitive("as.double")(fam4)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `fam5`.
## x NAs introduced by coercion
## ℹ Input `fam5` is `.Primitive("as.double")(fam5)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `fam6`.
## x NAs introduced by coercion
## ℹ Input `fam6` is `.Primitive("as.double")(fam6)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `test1`.
## x NAs introduced by coercion
## ℹ Input `test1` is `.Primitive("as.double")(test1)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `test2`.
## x NAs introduced by coercion
## ℹ Input `test2` is `.Primitive("as.double")(test2)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `test3`.
## x NAs introduced by coercion
## ℹ Input `test3` is `.Primitive("as.double")(test3)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `test4`.
## x NAs introduced by coercion
## ℹ Input `test4` is `.Primitive("as.double")(test4)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `lower1`.
## x NAs introduced by coercion
## ℹ Input `lower1` is `.Primitive("as.double")(lower1)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `lower2`.
## x NAs introduced by coercion
## ℹ Input `lower2` is `.Primitive("as.double")(lower2)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `higher1`.
## x NAs introduced by coercion
## ℹ Input `higher1` is `.Primitive("as.double")(higher1)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `higher2`.
## x NAs introduced by coercion
## ℹ Input `higher2` is `.Primitive("as.double")(higher2)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `control_shallow`.
## x NAs introduced by coercion
## ℹ Input `control_shallow` is `.Primitive("as.double")(control_shallow)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercion## Warning: Problem with `mutate()` input `control_deep`.
## x NAs introduced by coercion
## ℹ Input `control_deep` is `.Primitive("as.double")(control_deep)`.
## Caused by warning:
## ! NAs introduced by coercion## Warning in mask$eval_all_mutate(dots[[i]]): NAs introduced by coercioncodebook_dictionary <- rio::import("peril_data_deid_codebook.csv")
var_label(codebook_data) <- codebook_dictionary %>% select(variable, label) %>% dict_to_list()
metadata(codebook_data)$name <- 'Dataset Codebook'
metadata(codebook_data)$description <- "Data associated with paper 'Dangerous ground: One-year-old infants are sensitive to peril in other agents’ action plans'"
metadata(codebook_data)$creator <- "Shari Liu"
metadata(codebook_data)$datePublished <- "2022-04-12"
# omit the following lines, if your missing values are already properly labelled
# codebook_data <- detect_missing(codebook_data,
# only_labelled = TRUE, # only labelled values are autodetected as
# # missing
# negative_values_are_missing = FALSE, # negative values are missing values
# ninety_nine_problems = TRUE, # 99/999 are missing values, if they
# # are more than 5 MAD from the median
# )
# If you are not using formr, the codebook package needs to guess which items
# form a scale. The following line finds item aggregates with names like this:
# scale = scale_1 + scale_2R + scale_3R
# identifying these aggregates allows the codebook function to
# automatically compute reliabilities.
# However, it will not reverse items automatically.
# codebook_data <- detect_scales(codebook_data)Create codebook
skim_codebook(codebook_data)| Name | data |
| Number of rows | 286 |
| Number of columns | 40 |
| _______________________ | |
| Column type frequency: | |
| character | 13 |
| numeric | 27 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| sex | 0 | 1 | 1 | 1 | 0 | 2 | 0 |
| subj | 0 | 1 | 1 | 6 | 0 | 286 | 0 |
| experiment | 0 | 1 | 3 | 10 | 0 | 9 | 0 |
| exp_oldmapping | 0 | 1 | 5 | 10 | 0 | 8 | 0 |
| exp | 0 | 1 | 5 | 11 | 0 | 9 | 0 |
| cost | 0 | 1 | 3 | 8 | 0 | 4 | 0 |
| device | 0 | 1 | 0 | 6 | 204 | 3 | 0 |
| HV_side | 0 | 1 | 0 | 5 | 102 | 7 | 0 |
| first_test | 0 | 1 | 2 | 7 | 0 | 4 | 0 |
| first_fam | 0 | 1 | 2 | 4 | 0 | 4 | 0 |
| first_test_deeper_side | 0 | 1 | 0 | 5 | 144 | 3 | 0 |
| control_deeper_side | 0 | 1 | 0 | 5 | 144 | 3 | 0 |
| control_firstevent | 0 | 1 | 0 | 7 | 144 | 3 | 0 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | min | median | max | hist |
|---|---|---|---|---|---|---|---|---|
| reliability | 80 | 0.72 | 0.50 | 0.50 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▇ |
| agem | 0 | 1.00 | 11.24 | 1.67 | 8.97 | 10.33 | 15.67 | ▇▂▃▂▁ |
| video_quality | 206 | 0.28 | 4.88 | 0.33 | 4.00 | 5.00 | 5.00 | ▁▁▁▁▇ |
| audio_quality | 206 | 0.28 | 4.86 | 0.35 | 4.00 | 5.00 | 5.00 | ▁▁▁▁▇ |
| highchair | 204 | 0.29 | 0.46 | 0.50 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▇ |
| control_1 | 155 | 0.46 | 14.85 | 7.68 | 3.84 | 13.02 | 47.24 | ▇▆▂▁▁ |
| control_2 | 155 | 0.46 | 11.79 | 8.61 | 1.36 | 9.05 | 53.69 | ▇▃▁▁▁ |
| fam1 | 4 | 0.99 | 55.02 | 11.33 | 11.20 | 60.00 | 60.00 | ▁▁▁▁▇ |
| fam2 | 7 | 0.98 | 45.43 | 18.85 | 4.09 | 58.70 | 60.00 | ▂▂▁▁▇ |
| fam3 | 8 | 0.97 | 37.85 | 20.51 | 2.67 | 40.45 | 60.00 | ▃▃▂▂▇ |
| fam4 | 9 | 0.97 | 30.69 | 20.40 | 2.10 | 23.60 | 60.00 | ▇▆▃▃▇ |
| fam5 | 10 | 0.97 | 25.34 | 18.64 | 1.60 | 20.49 | 60.00 | ▇▆▃▂▅ |
| fam6 | 10 | 0.97 | 21.16 | 17.53 | 2.00 | 14.04 | 60.00 | ▇▃▂▁▂ |
| test1 | 9 | 0.97 | 26.16 | 16.90 | 3.31 | 21.15 | 60.00 | ▇▆▃▂▃ |
| test2 | 21 | 0.93 | 21.97 | 16.12 | 3.73 | 16.80 | 60.00 | ▇▅▂▂▂ |
| test3 | 40 | 0.86 | 19.10 | 15.45 | 1.71 | 13.25 | 60.00 | ▇▃▂▁▁ |
| test4 | 45 | 0.84 | 19.50 | 15.41 | 2.79 | 13.34 | 60.00 | ▇▃▁▁▁ |
| avg_fam | 1 | 1.00 | 36.00 | 11.41 | 8.72 | 34.96 | 60.00 | ▂▃▇▆▂ |
| sum_fam | 1 | 1.00 | 210.70 | 69.01 | 52.30 | 206.30 | 360.00 | ▂▅▇▆▂ |
| testavg_lower | 0 | 1.00 | 22.04 | 13.37 | 3.73 | 17.98 | 60.00 | ▇▆▃▂▁ |
| testavg_higher | 0 | 1.00 | 21.45 | 13.37 | 2.51 | 17.31 | 60.00 | ▇▇▅▂▂ |
| lower1 | 14 | 0.95 | 24.85 | 16.89 | 3.67 | 19.43 | 60.00 | ▇▆▃▂▂ |
| lower2 | 43 | 0.85 | 19.56 | 15.66 | 2.79 | 13.57 | 60.00 | ▇▃▂▁▁ |
| higher1 | 16 | 0.94 | 23.36 | 16.38 | 3.31 | 17.98 | 60.00 | ▇▆▂▂▂ |
| higher2 | 42 | 0.85 | 19.04 | 15.20 | 1.71 | 13.27 | 60.00 | ▇▃▁▁▁ |
| control_shallow | 154 | 0.46 | 14.11 | 8.68 | 1.61 | 11.81 | 53.69 | ▇▆▂▁▁ |
| control_deep | 156 | 0.45 | 12.56 | 7.83 | 1.36 | 10.27 | 39.93 | ▇▇▃▁▁ |
codebook(codebook_data)Metadata
Description
Dataset name: Dataset Codebook
Data associated with paper ‘Dangerous ground: One-year-old infants are sensitive to peril in other agents’ action plans’
Metadata for search engines
Date published: 2022-04-12
Creator:
| name | value |
|---|---|
| 1 | Shari Liu |
|
#Variables
reliability
whether this participant was randomly chosen for reliability coding
Distribution
Distribution of values for reliability
80 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| reliability | whether this participant was randomly chosen for reliability coding | numeric | 80 | 0.7202797 | 0 | 0 | 1 | 0.4951456 | 0.5011944 | ▇▁▁▁▇ |
sex
male or female
Distribution
Distribution of values for sex
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| sex | male or female | character | 0 | 1 | 2 | 0 | 1 | 1 | 0 |
subj
anonymized subject identity
Distribution
Distribution of values for subj
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| subj | anonymized subject identity | character | 0 | 1 | 286 | 0 | 1 | 6 | 0 |
agem
age in months
Distribution
Distribution of values for agem
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| agem | age in months | numeric | 0 | 1 | 9 | 10 | 16 | 11.24014 | 1.670372 | ▇▂▃▂▁ |
experiment
original name of experiment
Distribution
Distribution of values for experiment
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| experiment | original name of experiment | character | 0 | 1 | 9 | 0 | 3 | 10 | 0 |
exp_oldmapping
older, unused experiment naming in previous version of the paper
Distribution
Distribution of values for exp_oldmapping
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| exp_oldmapping | older, unused experiment naming in previous version of the paper | character | 0 | 1 | 8 | 0 | 5 | 10 | 0 |
exp
up to date name of experiment used in the paper
Distribution
Distribution of values for exp
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| exp | up to date name of experiment used in the paper | character | 0 | 1 | 9 | 0 | 5 | 11 | 0 |
cost
what kind of obstacle agent overcame in experiment (e.g. barrier, ramp, gap in LUTS, or danger in this paper)
Distribution
Distribution of values for cost
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| cost | what kind of obstacle agent overcame in experiment (e.g. barrier, ramp, gap in LUTS, or danger in this paper) | character | 0 | 1 | 4 | 0 | 3 | 8 | 0 |
video_quality
for online studies, caregiver rating of quality of stimulus videos
Distribution
Distribution of values for video_quality
206 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| video_quality | for online studies, caregiver rating of quality of stimulus videos | numeric | 206 | 0.2797203 | 4 | 5 | 5 | 4.875 | 0.3328055 | ▁▁▁▁▇ |
audio_quality
for online studies, caregiver rating of quality of stimulus sound
Distribution
Distribution of values for audio_quality
206 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| audio_quality | for online studies, caregiver rating of quality of stimulus sound | numeric | 206 | 0.2797203 | 4 | 5 | 5 | 4.85625 | 0.348539 | ▁▁▁▁▇ |
device
for online studies, what device was used to view the stimuli
Distribution
Distribution of values for device
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| device | for online studies, what device was used to view the stimuli | character | 0 | 1 | 3 | 204 | 0 | 6 | 0 |
highchair
for online studies, whether baby sat in a high chair for the duration of the experiment
Distribution
Distribution of values for highchair
204 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| highchair | for online studies, whether baby sat in a high chair for the duration of the experiment | numeric | 204 | 0.2867133 | 0 | 0 | 1 | 0.4634146 | 0.5017284 | ▇▁▁▁▇ |
HV_side
which side the higher value agent was on, or what side the deeper cliff was on
Distribution
Distribution of values for HV_side
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| HV_side | which side the higher value agent was on, or what side the deeper cliff was on | character | 0 | 1 | 7 | 102 | 0 | 5 | 0 |
first_test
first test event
Distribution
Distribution of values for first_test
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| first_test | first test event | character | 0 | 1 | 4 | 0 | 2 | 7 | 0 |
first_fam
first familiarization event
Distribution
Distribution of values for first_fam
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| first_fam | first familiarization event | character | 0 | 1 | 4 | 0 | 2 | 4 | 0 |
first_test_deeper_side
for Exp 2, the left-right arrangement of the deeper and shallower trench during the first test trial
Distribution
Distribution of values for first_test_deeper_side
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| first_test_deeper_side | for Exp 2, the left-right arrangement of the deeper and shallower trench during the first test trial | character | 0 | 1 | 3 | 144 | 0 | 5 | 0 |
control_deeper_side
the left-right arrangement of the deeper and shallower trench during the control event
Distribution
Distribution of values for control_deeper_side
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| control_deeper_side | the left-right arrangement of the deeper and shallower trench during the control event | character | 0 | 1 | 3 | 144 | 0 | 5 | 0 |
control_firstevent
which event came first during control event
Distribution
Distribution of values for control_firstevent
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| control_firstevent | which event came first during control event | character | 0 | 1 | 3 | 144 | 0 | 7 | 0 |
control_1
looking time during first control event
Distribution
Distribution of values for control_1
155 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| control_1 | looking time during first control event | numeric | 155 | 0.458042 | 3.8 | 13 | 47 | 14.85113 | 7.675728 | ▇▆▂▁▁ |
control_2
looking time during second control event
Distribution
Distribution of values for control_2
155 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| control_2 | looking time during second control event | numeric | 155 | 0.458042 | 1.4 | 9.1 | 54 | 11.79247 | 8.607699 | ▇▃▁▁▁ |
fam1
looking time during familiarization
Distribution
Distribution of values for fam1
4 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| fam1 | looking time during familiarization | numeric | 4 | 0.986014 | 11 | 60 | 60 | 55.01654 | 11.33048 | ▁▁▁▁▇ |
fam2
looking time during familiarization
Distribution
Distribution of values for fam2
7 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| fam2 | looking time during familiarization | numeric | 7 | 0.9755245 | 4.1 | 59 | 60 | 45.42599 | 18.84502 | ▂▂▁▁▇ |
fam3
looking time during familiarization
Distribution
Distribution of values for fam3
8 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| fam3 | looking time during familiarization | numeric | 8 | 0.972028 | 2.7 | 40 | 60 | 37.85457 | 20.50916 | ▃▃▂▂▇ |
fam4
looking time during familiarization
Distribution
Distribution of values for fam4
9 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| fam4 | looking time during familiarization | numeric | 9 | 0.9685315 | 2.1 | 24 | 60 | 30.69409 | 20.4046 | ▇▆▃▃▇ |
fam5
looking time during familiarization
Distribution
Distribution of values for fam5
10 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| fam5 | looking time during familiarization | numeric | 10 | 0.965035 | 1.6 | 20 | 60 | 25.3413 | 18.639 | ▇▆▃▂▅ |
fam6
looking time during familiarization
Distribution
Distribution of values for fam6
10 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| fam6 | looking time during familiarization | numeric | 10 | 0.965035 | 2 | 14 | 60 | 21.16081 | 17.525 | ▇▃▂▁▂ |
test1
looking time during test
Distribution
Distribution of values for test1
9 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| test1 | looking time during test | numeric | 9 | 0.9685315 | 3.3 | 21 | 60 | 26.15703 | 16.89635 | ▇▆▃▂▃ |
test2
looking time during test
Distribution
Distribution of values for test2
21 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| test2 | looking time during test | numeric | 21 | 0.9265734 | 3.7 | 17 | 60 | 21.97015 | 16.11725 | ▇▅▂▂▂ |
test3
looking time during test
Distribution
Distribution of values for test3
40 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| test3 | looking time during test | numeric | 40 | 0.8601399 | 1.7 | 13 | 60 | 19.10359 | 15.44814 | ▇▃▂▁▁ |
test4
looking time during test
Distribution
Distribution of values for test4
45 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| test4 | looking time during test | numeric | 45 | 0.8426573 | 2.8 | 13 | 60 | 19.50339 | 15.41324 | ▇▃▁▁▁ |
avg_fam
average looking time during familiarization (fam 1-6)
Distribution
Distribution of values for avg_fam
1 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| avg_fam | average looking time during familiarization (fam 1-6) | numeric | 1 | 0.9965035 | 8.7 | 35 | 60 | 36.00463 | 11.41305 | ▂▃▇▆▂ |
sum_fam
total looking time during familiarization (fam 1-6)
Distribution
Distribution of values for sum_fam
1 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| sum_fam | total looking time during familiarization (fam 1-6) | numeric | 1 | 0.9965035 | 52 | 206 | 360 | 210.698 | 69.01051 | ▂▅▇▆▂ |
testavg_lower
average looking time towards the lower value or lower danger test event
Distribution
Distribution of values for testavg_lower
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| testavg_lower | average looking time towards the lower value or lower danger test event | numeric | 0 | 1 | 3.7 | 18 | 60 | 22.04001 | 13.37239 | ▇▆▃▂▁ |
testavg_higher
average looking time towards the higher value or higher danger test event
Distribution
Distribution of values for testavg_higher
0 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| testavg_higher | average looking time towards the higher value or higher danger test event | numeric | 0 | 1 | 2.5 | 17 | 60 | 21.44526 | 13.37161 | ▇▇▅▂▂ |
lower1
looking time during the first lower value or lower danger test event
Distribution
Distribution of values for lower1
14 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| lower1 | looking time during the first lower value or lower danger test event | numeric | 14 | 0.951049 | 3.7 | 19 | 60 | 24.85424 | 16.88764 | ▇▆▃▂▂ |
lower2
looking time during the seoncd lower value or lower danger test event
Distribution
Distribution of values for lower2
43 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| lower2 | looking time during the seoncd lower value or lower danger test event | numeric | 43 | 0.8496503 | 2.8 | 14 | 60 | 19.56239 | 15.659 | ▇▃▂▁▁ |
higher1
looking time during the first higher value or higher danger test event
Distribution
Distribution of values for higher1
16 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| higher1 | looking time during the first higher value or higher danger test event | numeric | 16 | 0.9440559 | 3.3 | 18 | 60 | 23.36013 | 16.37809 | ▇▆▂▂▂ |
higher2
looking time during the second higher value or higher danger test event
Distribution
Distribution of values for higher2
42 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| higher2 | looking time during the second higher value or higher danger test event | numeric | 42 | 0.8531469 | 1.7 | 13 | 60 | 19.04155 | 15.19846 | ▇▃▁▁▁ |
control_shallow
looking time during control event involving shallow cliff
Distribution
Distribution of values for control_shallow
154 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| control_shallow | looking time during control event involving shallow cliff | numeric | 154 | 0.4615385 | 1.6 | 12 | 54 | 14.10883 | 8.681716 | ▇▆▂▁▁ |
control_deep
looking time during control event involving deeper cliff
Distribution
Distribution of values for control_deep
156 missing values.
Summary statistics
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| control_deep | looking time during control event involving deeper cliff | numeric | 156 | 0.4545455 | 1.4 | 10 | 40 | 12.56002 | 7.832928 | ▇▇▃▁▁ |
Missingness report
Codebook table
JSON-LD metadata
The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.
{
"name": "Dataset Codebook",
"description": "Data associated with paper 'Dangerous ground: One-year-old infants are sensitive to peril in other agents’ action plans'\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
"creator": "Shari Liu",
"datePublished": "2022-04-12",
"keywords": ["reliability", "sex", "subj", "agem", "experiment", "exp_oldmapping", "exp", "cost", "video_quality", "audio_quality", "device", "highchair", "HV_side", "first_test", "first_fam", "first_test_deeper_side", "control_deeper_side", "control_firstevent", "control_1", "control_2", "fam1", "fam2", "fam3", "fam4", "fam5", "fam6", "test1", "test2", "test3", "test4", "avg_fam", "sum_fam", "testavg_lower", "testavg_higher", "lower1", "lower2", "higher1", "higher2", "control_shallow", "control_deep"],
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "reliability",
"description": "whether this participant was randomly chosen for reliability coding",
"@type": "propertyValue"
},
{
"name": "sex",
"description": "male or female",
"@type": "propertyValue"
},
{
"name": "subj",
"description": "anonymized subject identity",
"@type": "propertyValue"
},
{
"name": "agem",
"description": "age in months",
"@type": "propertyValue"
},
{
"name": "experiment",
"description": "original name of experiment",
"@type": "propertyValue"
},
{
"name": "exp_oldmapping",
"description": "older, unused experiment naming in previous version of the paper",
"@type": "propertyValue"
},
{
"name": "exp",
"description": "up to date name of experiment used in the paper",
"@type": "propertyValue"
},
{
"name": "cost",
"description": "what kind of obstacle agent overcame in experiment (e.g. barrier, ramp, gap in LUTS, or danger in this paper)",
"@type": "propertyValue"
},
{
"name": "video_quality",
"description": "for online studies, caregiver rating of quality of stimulus videos",
"@type": "propertyValue"
},
{
"name": "audio_quality",
"description": "for online studies, caregiver rating of quality of stimulus sound",
"@type": "propertyValue"
},
{
"name": "device",
"description": "for online studies, what device was used to view the stimuli",
"@type": "propertyValue"
},
{
"name": "highchair",
"description": "for online studies, whether baby sat in a high chair for the duration of the experiment",
"@type": "propertyValue"
},
{
"name": "HV_side",
"description": "which side the higher value agent was on, or what side the deeper cliff was on",
"@type": "propertyValue"
},
{
"name": "first_test",
"description": "first test event",
"@type": "propertyValue"
},
{
"name": "first_fam",
"description": "first familiarization event",
"@type": "propertyValue"
},
{
"name": "first_test_deeper_side",
"description": "for Exp 2, the left-right arrangement of the deeper and shallower trench during the first test trial",
"@type": "propertyValue"
},
{
"name": "control_deeper_side",
"description": "the left-right arrangement of the deeper and shallower trench during the control event",
"@type": "propertyValue"
},
{
"name": "control_firstevent",
"description": "which event came first during control event",
"@type": "propertyValue"
},
{
"name": "control_1",
"description": "looking time during first control event",
"@type": "propertyValue"
},
{
"name": "control_2",
"description": "looking time during second control event",
"@type": "propertyValue"
},
{
"name": "fam1",
"description": "looking time during familiarization",
"@type": "propertyValue"
},
{
"name": "fam2",
"description": "looking time during familiarization",
"@type": "propertyValue"
},
{
"name": "fam3",
"description": "looking time during familiarization",
"@type": "propertyValue"
},
{
"name": "fam4",
"description": "looking time during familiarization",
"@type": "propertyValue"
},
{
"name": "fam5",
"description": "looking time during familiarization",
"@type": "propertyValue"
},
{
"name": "fam6",
"description": "looking time during familiarization",
"@type": "propertyValue"
},
{
"name": "test1",
"description": "looking time during test",
"@type": "propertyValue"
},
{
"name": "test2",
"description": "looking time during test",
"@type": "propertyValue"
},
{
"name": "test3",
"description": "looking time during test",
"@type": "propertyValue"
},
{
"name": "test4",
"description": "looking time during test",
"@type": "propertyValue"
},
{
"name": "avg_fam",
"description": "average looking time during familiarization (fam 1-6)",
"@type": "propertyValue"
},
{
"name": "sum_fam",
"description": "total looking time during familiarization (fam 1-6)",
"@type": "propertyValue"
},
{
"name": "testavg_lower",
"description": "average looking time towards the lower value or lower danger test event",
"@type": "propertyValue"
},
{
"name": "testavg_higher",
"description": "average looking time towards the higher value or higher danger test event",
"@type": "propertyValue"
},
{
"name": "lower1",
"description": "looking time during the first lower value or lower danger test event",
"@type": "propertyValue"
},
{
"name": "lower2",
"description": "looking time during the seoncd lower value or lower danger test event",
"@type": "propertyValue"
},
{
"name": "higher1",
"description": "looking time during the first higher value or higher danger test event",
"@type": "propertyValue"
},
{
"name": "higher2",
"description": "looking time during the second higher value or higher danger test event",
"@type": "propertyValue"
},
{
"name": "control_shallow",
"description": "looking time during control event involving shallow cliff",
"@type": "propertyValue"
},
{
"name": "control_deep",
"description": "looking time during control event involving deeper cliff",
"@type": "propertyValue"
}
]
}`